Collaborative Research: High Performance Parallel Processing: Fault-Tolerant Computing on a Network of Workstations

该项目涉及并行处理中的理论和原型研究，以利用工作站集群的能力。主要技术将基于积极的调度、闪存和分散的数据管理。该形式化工作在以下几个方面扩展了PIS在异步计算中的前人成果：(1)将模型扩展到模型，再扩展到细粒度程序。(2)允许将建筑特定特征纳入理论框架。(3)区分由超时、中断和故障(或计算的无限期延迟)导致的不同处理器所看到的存储器状态不一致的技术。(4)允许非确定性执行的技术。(5)对容错程序的输入输出操作进行建模。该项目的实验部分将构建一个可扩展的版本，以便在工作站集群上执行并行程序。原型将解决与线程的紧急调度、闪存的实现和数据管理相关的问题。原型将试图从效率的角度评估环境的有效性。这个项目是由亚利桑那州立大学的P.Dasgupta和纽约大学的Z.Kedem共同进行的。

This project deals with both theoretical and prototyping research in parallel processing to harness the power of workstation clusters. The primary techniques will based on aggressive scheduling, evasive memory and dispersed data management. The formal work expands the previous results of the PIS in asynchronous computing in several directions: (1) Extend the models to models to fine-grained programs. (2) Permit the inclusion of architecture specific characteristics into theoretical frameworks. (3) Techniques to distinguish inconsistencies in memory states as viewed by different processors resulting from time-outs, interrupts and failures (or indefinite postponement of a computation). (4) Techniques to allow non-deterministic executions. (5) Model input/output operations of fault-tolerant programs. Thee experimental part of the project will build a scaled version to execute parallel programs on clusters of workstations. The prototype will address issues related to the eager scheduling of threads, the implementation of evasive memory and data management. The prototype will attempt to evaluate the effectiveness of the environment in terms of efficiency. This project is conducted jointly by P. Dasgupta of Arizona State University and Z. Kedem, of New York University.